{"id":"W3125944741","doi":"10.2139/ssrn.2236709","title":"GARCH Models for Daily Stock Returns: Impact of Estimation Frequency on Value-at-Risk and Expected Shortfall Forecasts","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Expected shortfall; Value at risk; Autoregressive conditional heteroskedasticity; Stock (firearms); Econometrics; Economics; Estimation; Financial economics; Volatility (finance); Risk management; Geography; Finance; Portfolio","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01873712,0.0008154491,0.001656234,0.001288601,0.0005983396,0.002106132,0.001368432,0.001895625,0.002543416],"category_scores_gemma":[0.0701232,0.001002909,0.001146112,0.001067638,0.0006067395,0.004596439,0.0008868458,0.002602829,0.0007372086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005051765,"about_ca_system_score_gemma":0.0005891885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003144921,"about_ca_topic_score_gemma":0.002963453,"domain_scores_codex":[0.9957827,0.003070157,0.0001721753,0.0003725496,0.0004271885,0.0001752172],"domain_scores_gemma":[0.8783014,0.1111154,0.00305864,0.005316397,0.001806122,0.0004020201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001139961,0.0001692561,0.01394978,0.00009688172,0.0004267998,0.0001209122,0.0001516841,0.9133246,0.001127467,0.007145995,0.001449572,0.06089703],"study_design_scores_gemma":[0.00004352033,0.00007633417,0.002340867,0.00001364152,0.00006553868,0.00003605431,0.00001854929,0.990397,0.0004515154,0.006349647,0.0001858543,0.00002151119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6372707,0.00270741,0.3544573,0.001264314,0.000241958,0.0000571675,0.0006721524,0.001404525,0.001924476],"genre_scores_gemma":[0.9548312,0.001078712,0.04147695,0.0001270732,0.0002441283,0.00004446818,0.0007537774,0.0002162537,0.001227541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01873712,"threshold_uncertainty_score":0.09909254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02837781610074806,"score_gpt":0.2542831570678562,"score_spread":0.2259053409671081,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}